Accelerating Science with Open Source, sponsored by OSSci

Our planet is facing many existential threats. In order to tackle these challenges, we will require a lot of science over the coming years and decades. But without a strong open source foundation, it will take that much longer and cost that much more.

Meet Open-Source Science (OSSci), a new NumFOCUS initiative that aims to accelerate scientific research and discovery through better open source in science.

OSSci was launched at the SciPy conference in July 2022. Our interest groups – initially focused on material sciences/chemistry, life sciences/healthcare, and climate/sustainability have been getting under way.

We want to meet scientists who are using open source successfully in their work. And we want to hear from OSS developers who work on science-related projects.

Abby Mitchell
Developer Advocate, IBM Quantum
Qiskit: a Quantum Information Science Kit
Quantum computing is an exciting emerging technology with potential applications in a range of scientific fields. In this talk we will introduce Qiskit, an open-source SDK created by IBM to support users conducting research on quantum devices.

Tom Nicholas
Research software engineer at Lamont-Doherty Earth Observatory, Columbia University
Xarray-Datatree: Hierarchical Data Structures for Multi-Model Science
Scientific data analysis often involves many related but distinct multi-dimensional datasets - xarray-DataTree organises these in-memory allowing for expressive analysis of complex datasets.

Lucy Hyde
Program Manager, Machine Learning at the Linux Foundation
An Open Source Approach to Improving Global Agriculture Efficiency: The Integrated PyTorch-AgStack Project
Discussing an upcoming collaboration between PyTorch and AgStack, a Linux Foundation project focusing on improving global agriculture efficiency, and partnership with the Food and Agriculture Organization (UN) and MIT. The collaboration will explore combining PyTorch with field data layers from India and Zimbabwe to create a registry of agricultural fields to assist in carbon tracking, food tracking and crop production, and other metrics.

Dr. Julius Busecke (he/him)
Senior Staff Associate, Columbia University, Manager of Data and Computing, LEAP, Lead of Open Research, M²LInES
“Beyond just open - Modern science should be creative, fast, and fun for everyone"
Using climate science as an example, I will make the point that open source software, coupled with analysis-ready cloud-optimized data and scalable compute, has transformed who can participate in the scientific discourse and accelerate scientific discovery by enabling creative, fast, and fun science on big data.

Johannes Schmude
Research Staff Member, IBM
Combining array- and columnar stores for rapid discovery across climate, weather and earth observation data
Conventional approaches to geo-spatiotemporal data stores deal primarily with the question of where and when. Given an area and a time range, a user can efficiently retrieve the corresponding data. However, many questions in climate and sustainability start with a search: "When and where do we expect climate extremes?" "What satellite imagery is available for which our assets are not obstructed by clouds?" and so on. In the face of these, one often reverts to table scans on the raw data. In this talk, we will show how one can combine columnar stores such as parquet with array stores like zarr to achieve massive acceleration of such discovery tasks.

Lightning talk format (5-8 minutes).

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RSVP is required, please note that walk-ins will not be accepted.
Doors @ 5:30 pm
Event @ 6:00 - 8:30 pm
Venue provided by IBM: 590 Madison Ave
Catering (food & drinks) sponsored by Open Source Science (OSSci).
Thank you, IBM & OSSci!
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The entrance is on the corner of E 56th Street and Madison Ave.
The building requires a government-issued photo ID for entrance.

This, and all PyData NYC events, is an all-levels event. Newcomers and beginners are welcome.
This, and all NumFOCUS-affiliated events and spaces, both in-person and online are governed by a Code of Conduct. More at https://pydata.org/code-of-conduct/
This event will not be recorded.